Motion artifact correction of tomographical images

ABSTRACT

The invention relates to a method in which the information contents of an image of a moving object is enhanced. The invention also relates to a system in which such a method can be carried out and to a computer program enabling a data processing unit to carry out such a method. The method is used notably in the field of medical imaging systems. According to the method first a first image of a moving object is acquired by means of a first imaging method, said image containing artifacts which are caused by the object motion. From two further images, acquired by means of a second imaging respective state of motion of the motion, there is formed a motion model which is implemented in a different manner in image processing or image forming steps, so that the information contents of either the first image or a combination image, formed from the first image and the two further images, is enhanced.

The invention relates to a method of enhancing the information contentsof an image of a moving object. The invention also relates to a systemin which a method of this kind is carried out as well as to a computerprogram enabling a data processing unit to carry out such a method. Thismethod is used notably in the field of medical imaging systems.

A method of this kind is applied wherever images of a moving object areto be formed, which images often contain unavoidable motion artifacts.As a result, the object is usually imaged in a blurred fashion so thatit offers a viewer only inadequate information concerning the object.Motion artifacts often give rise to unusable images in particular in thecase of slice images or volume images of a moving object.

The article by D. Mattes et al. “Nonrigid multimodality imageregistration”, Medical imaging 2001: Image Processing, Proceedings ofSPE vol. 4322 (2001), discloses a method in which an image of a movingobject, acquired and reconstructed by means of the PET method andcontaining motion artifacts, is superposed on a further image of themoving object, acquired and reconstructed by means of the CT method, soas to form a combination image. The combination image is formed byspecial registration of the two individual images while utilizingpregnant, bilateral similarity information contained in both images.Because of the physical circumstances, the PET image contains pronouncedmotion artifacts which are not taken into account in the disclosedmethod and give rise to problems during the registration.

It is an object of the invention to increase the information content ofimages containing motion artifacts.

This object is achieved in accordance with the invention by means of amethod of enhancing the information contents which can be derived from afirst image, containing motion artifacts, of a moving object, whichmethod includes the following steps:

-   a. using two further images which represent the object in a    respective state of motion with as few motion artifacts as possible,-   b. determining a motion model which characterizes states of motion    assumed by the object while performing the motion between the two    states of motion.    The first image may have to be reconstructed from projections.

There is a first image of a moving object which contains motionartifacts which are due to the motion of the object. Motion artifactsare the cause, for example, that the object is imaged less sharply asthe object has moved more during the acquisition time. Such motionartifacts may occur when the acquisition time of the imaging method usedfor the acquisition is long in comparison with the motion, so that theobject moves during the acquisition. The term “motion” is to beinterpreted in a very broad sense. The object may perform, for example,a very complex natural motion (human heart) or merely a linear, uniformmotion (a sphere rolling at a constant speed).

Furthermore, at least two further images of the object are involved.Each of these images represents a respective state of motion of theobject and is as free from motional artifacts as possible, the twostates of motions originating from the motion performed by the objectduring the acquisition of the first image. Alternatively, the two statesof motions represented may also originate from a motion which has beenperformed by the object at a different instant and is at leastapproximately the same as the motion performed by the object during theacquisition of the first image. In order to image the states of motionwith as few artifacts as possible, the acquisition time is generallyshort in comparison with the duration of the motion.

The imaging methods that can be used for the acquisition of the firstimage and the two further images may be the same or be different. When acommon imaging method is used for all images, the differentcharacteristics of the first image and of the two further images can berealized by way of different adjustments of acquisition parameters. Whentwo different imaging methods are used, each of which reproduces othercharacteristics of the object, information of such differentcharacteristics can be advantageously supplemented at a later stage.

There is also determined a motion model of the motion of the objectwhich characterizes states of motion assumed by the object whileperforming the motion between the two states of motion. In particular inthe case of a complex natural motion of the object, individual parts ofthe object move differently during the execution of the motion; forexample, some parts of the object travel only a short distance whereasother parts follow a long and possibly curved path. Starting from of oneof the two states of motion, the motion model describes the behavior fordifferent parts of the object during the motion from one state of motionto the other.

The information thus obtained as regards the motion of the object can beincorporated in various ways in supplementary image processing or imageforming steps, resulting in a higher quality of the resultant images.

For example, such supplementary steps in accordance with the inventionas disclosed in claim 1 are:

-   c. forming an intermediate image of the object from the motion model    and the two further images, the intermediate image representing the    object at least approximately as if it had performed the motion,-   d. forming a combination image from the intermediate image and the    first image.

The intermediate image formed represents the object as if it were toperform the motion. To this end, starting from the two known states ofmotion, the object motion is imitated by means of the motion model andthe intermediate image is formed from this information, for example, bysuperposition. The intermediate image thus reconstructed represents theobject with substantially the same motion artifacts as the first image.

A viewer may wish to view the first image with as few falsifications aspossible, despite the motion artifacts contained therein, becauseinformation may be lost in the course of known image processing methods.The superposition of the intermediate image and the first image so as toform a combination image then offers the advantage that on the one handthe first image is presented with as few falsifications as possiblewhereas on the other hand the information from the two further images isprepared in the intermediate image in such a manner that it can becombined directly with the information of the first image.

The combination can be carried out in a variety of manners. For example,the two images can be additively superposed, so that the relevantinformation of the individual images is represented in an overall image.The variable division of the combination image constitutes a furtherpossibility, a part of the combination image then being represented bythe intermediate image whereas the other part is represented by thefirst image. A viewer can then move the boundary between the twosub-regions, so that an object detail is represented once by theintermediate image and once by the first image. Alternatively, thesub-regions can also be displayed so as to be separated by a window, thewindow being displaceable across the combination image by means of acontrol unit. A simple method of forming the combination image consistsin arranging the intermediate image and the first image adjacent oneanother so that the two images are simultaneously presented to theviewer.

A further supplementary step in accordance with claim 2 consists of:

-   c. focusing the first image by means of the motion model.

During the focusing the motion artifacts are reduced to such an extentthat the object represented in the first image is presented sharply to aviewer. Generally speaking, the object appears to be unsharp to a viewerbecause several states of motion of the object motion are represented insuperposed form in an image. For the focusing of an object representedwith motional unsharpness, the object is represented in only one stateof motion of the motion in that the superposition with the remainingstates of motion is eliminated. This is possible when the motion leadingto the unsharp representation is known. The motion model of the objectmotion determined in the first step contains exactly this informationconcerning the object motion, and a focusing algorithm can utilizeinformation from the motion model for focusing. This results in an imagewhich represents the object in one state of motion (that is sharply) andappears to the viewer as if it has been acquired by means of the firstimaging method. This is advantageous in particular when the firstimaging method is not suitable, for example, for physical reasons, toacquire a sharp image of the moving object.

When the first image is to be reconstructed from projections, inconformity with claim 3 there are the following supplementary steps:

-   c. forming an intermediate image of the object from the motion model    and the two further images, the intermediate image representing the    object at least substantially as if it had performed the motion,-   d. reconstructing the first image from the projections of the object    and the intermediate image.

For this method to be used it is necessary that, instead of a firstimage, projections of the moving object are available first and that thefirst image is reconstructed from these projections, for example, bymeans of a data processing unit. Methods of this kind are known interalia from the field of medical slice or volume imaging, such as computedtomography, magnetic resonance tomography or positron emissiontomography.

In particular in the case of radiation-emitting object, as used forimaging in the case of positron emission tomography, the fact must betaken into account that a part of this radiation is absorbed by otherparts of the object. Methods are known which take into accountinformation concerning such so-called location-specific attenuation forthe reconstruction in order to avoid artifacts in the reconstructedimage. To this end, usually a transmission image of the object ifformed, which transmission image represents the necessarylocation-specific attenuations. It is a drawback, however, inter aliathat the motions of the object, leading to artifacts in the first image,are not or not adequately present in the transmission image so that theycannot be taken into account for the reconstruction. This leads toartifacts in the reconstructed image.

From two points of view it is particularly advantageous to utilize theintermediate image during the reconstruction: on the one hand, theintermediate image contains the necessary information forlocation-specific attenuation and on the other hand the motion of theobject, being present in the intermediate image, is taken into account.The images reconstructed with the aid of such an intermediate image havean enhanced quality in comparison with images reconstructed by means ofconventional transmission images. Therefore, the intermediate imageshould generally contain information concerning the formation of theimage by means of the first imaging method, in this case beinginformation as regards the location-specific attenuation.

It is to be noted that in particular the methods in conformity with theclaims 1 and 3 or the claims 2 and 3 can be combined and that theyadvantageously supplement one another.

In particular in the case of objects whose parts move differently therepresentation by way of motion vector fields in conformity with claim 4offers a simple and adequate location-specific representation of thenecessary information for the remainder of the method. A motion vectorfield indicates how or along which path the corresponding part of anobject moves while performing the motion between the two known states ofmotion.

When it is known how often the relevant states of motion are assumed bythe object while performing the motion, or how long the relative stay isof the object in the relevant state of motion, the generating of theintermediate image is particularly simple in conformity with claim 5.Such information can be based, for example, on a model of the motion orbe determined by means of a sensor while the motion is performed. Suchformation of the intermediate image offers the advantage that it is notnecessary to describe the entire motion in the motion model, but onlyinformation concerning individual states of motion as well as theirfrequency.

Because of the use of different imaging methods it may occur that theindividual parts of the object in the intermediate image are differentlylocalized relative to the first image. Relative differences between theobject parts themselves as well as absolute differences relative to theimage edges or ratio of dimensions of the object parts may then occur.In other words, the object is represented in the intermediate image witha co-ordinate system which differs from that in the first image. Theregistration as disclosed in claim 6 enables the relevant parts of theobject to be transformed either from the positions represented in theintermediate image to the positions represented in the first image orvice versa. All parts of the object are then in the same image positionsin the intermediate image as well as in the first image, thus enablingsuperposition of the two images.

An additional step in accordance with the invention enables the objectrepresented in the combination image to be represented in a selectedstate of motion of the motion. To this end, known focusing algorithmsare used in combination with the motion model and/or one of the twofurther images. The state of motion then represented can correspond, inconformity with the focusing algorithm used, any state of motion of themotion, but notably the states of motion represented in the two furtherimages.

An advantageous further version of the method of claim 2 is disclosed inclaim 8. A viewer is not only offered the sharper first image, butadditionally a comparison with one of the two further images is madepossible.

The method in accordance with the invention can in principle be carriedout by means of two imaging methods which are based on the samemodality. As opposed thereto, the use of different modalities enablesthe representation of different characteristics of the moving object inthe corresponding images. The method in accordance with the invention isadvantageously used in conformity with claim 9 when the first imagingmethod cannot offer images of a moving object without motion artifacts.

The object is also achieved by means of the system as disclosed in claim10. An image processing system is to be understood to mean any systemcapable of receiving the images or the data formed by the method inaccordance with the invention, of processing these images or dataaccordingly, and of either visualizing the result or applying it toother systems. The image processing system may be completely independentfrom the devices acquiring the image data by means of the relevantimaging methods. On the other hand it is also feasible to construct theimage processing system as a component of a larger system. The dataprocessing unit may optionally be constructed so as to be programmable.

The object is also achieved by means of an examination system asdisclosed in claim 11. The devices for forming the images are well knownfrom prior art so that they will not be elaborated herein. By way ofexample there may be mentioned: X-ray systems, magnetic resonancetomography apparatus and apparatus from the field of nuclear medicine.The two imaging methods may be realized by means of a common modality ofby means of different modalities. The difference will be illustrated onthe basis of the following example: a common modality is assumed to be aconventional X-ray fluoroscopy where the first imaging method producesimages containing motion artifacts during a long acquisition time andwith a low dose, and the second imaging method produces images during ashort acquisition time and with a higher dose. Depending on theconstruction of the examination apparatus, the two imaging methods canbe carried out by means of the same device by variation of the relevantparameters. When different modalities are used, one device may be, forexample, a computed tomography apparatus and the other device a PETsystem.

If the data processing unit of a system as described above isconstructed so as to be programmable, a computer program as disclosed inclaim 12 enables the data processing unit to carry out a method inaccordance with the invention. Depending on the configuration, thecomputer program can be made available to the data processing unit bymeans of a computer program product such as an external, portablestorage medium.

The following examples and embodiments are illustrated with reference tothe FIGS. 1 to 6. Therein

FIG. 1 shows the block diagram of a version of the method in conformitywith claim 1,

FIG. 2 shows the block diagram of a version of the method in conformitywith claim 2,

FIG. 3 shows the block diagram of a version of the method in conformitywith claim 3,

FIG. 4 shows, by way of example, the states of motion of humanrespiration,

FIG. 5 shows the state of motion function of a uniform motion, and

FIG. 6 shows a PET-CT combination system.

The FIGS. 1 to 3 show the steps of a number of versions of the method inaccordance with the invention. The rectangular boxes represent results,data, images etc. Steps of the methods are stated within an ellipse.

FIG. 1 is a diagrammatic representation of the steps and results of afirst version of the method. It is an object of the method to acquireimages of a moving object by means of two different imaging methods, inthis case being methods based on PET and CT. The different imagingmethods enable different information to be acquired as regards themoving object. Such different information is to be presented in commonto a user.

Projections P1 which have been made, for example, of the thorax of apatient at the area of the diaphragm by means of the PET (PositronEmission Tomography) method are available (the method itself is notshown in FIG. 1). The PET method is known from the field of nuclearmedicine and is intended for the formation of slice images or volumeimages. A metabolic preparation, marked with given, unstable nuclides,is then injected into a patient, said preparation being taken up in atissue-specific or function-specific manner. The radio nuclides useddecay, giving rise to two γ quanta in different successive processes inthe vicinity of the location of decay, which quanta take off in exactlyopposite directions, leave the patient and can be detected by suitablesensors which are arranged in a detector in the form of a ring aroundthe patient. On their travel from their location of origin to theirpoint of emergence from the patient the γ quanta traverse further tissueof the patient which can absorb the γ quanta more or less as a functionof the type of tissue. Generally speaking, the γ quanta are attenuatedin a tissue-specific manner. The whole of detected γ quanta forms a setof projections P1 of the object wherefrom a slice image or volume imagecan be reconstructed in known manner during a subsequent reconstruction.The PET method yields functional images of the object.

During the acquisition of the projections P1, which may last from a fewminutes to one hour, the patient performs a respiratory motion duringwhich the diaphragm moves in conformity with the respiration. Thisrespiratory motion causes motion artefacts in the reconstructed PETimage I0, said artifacts becoming manifest as an unsharp and blurredimage of the object. At least two causes of such motion artifacts areknown:

-   1) Because of the respiratory motion, a given location of a tissue    occupies different positions relative to the detector, so that γ    quanta arising at this location are acquired by different sensors of    the detector.-   2) γ quanta which successively arise in substantially the same    location are attenuated to a different extent, because the relative    position of the surrounding tissue, which is responsible for the    attenuation, changes relative to the location of origin of the X-ray    quanta due to the respiratory motion.

Also available are the images I2 and I3 which have been acquired bymeans of the CT-based method which is not shown in FIG. 1. The CT(Computed Tomography) method is known, for example, from the medicalfield and serves to form slice images and volume images of objects orpatients, such images containing anatomical information. A CT-basedsystem will be described in detail hereinafter. As opposed to PETimages, CT images contain substantially fewer or no motion artifacts,because the image acquisition can take place substantially faster inrelation to the motion. Known systems, combining PET images withfunctional information on the object and CT images with anatomicalinformation on the object, ignore the motion artifacts of the PET imagesupon combination of the information, so that the combined informationincludes further artifacts or errors. These artifacts or errors aresignificantly reduced by means of the invention. In the further courseof this description it will be demonstrated how artifacts which arise inthe PET image due to the above cause 1) are taken into account in thecombined information.

In order to illustrate the acquisition of such images, FIG. 6 shows, byway of example, a combination system which consists of a computedtomography apparatus and a PET system. The computed tomography apparatusand the PET system are both configured in principle as independentsystems which, however, are geometrically coupled relative to a commonaxis of reference. For the image acquisition the systems are usuallyused consecutively; for example, first CT images, representing twostriking states of motion, are acquired and subsequently the acquisitionof the PET data takes place.

The computed tomography apparatus includes a gantry 1 which is capableof rotation around an axis of rotation 14 which extends parallel to thez direction. To this end, the gantry 1 is driven at a preferablyconstant but adjustable angular speed by a motor 2. A radiation sourceS, for example, an X-ray tube, is attached to the gantry 1. Theradiation source is provided with a collimator arrangement 3 which formsa conical radiation beam 4 from the radiation produced by the radiationsource S. The radiation beam 4 penetrates a moving object (not shown)which is present in a cylindrical examination zone 13. After havingtraversed the examination zone 13, the X-ray beam 4 is incident on atwo-dimensional detector unit 16 attached to the gantry 1.

The angle of aperture α_(max) of the radiation beam 4 (the angle ofaperture is defined as the angle enclosed by a ray of the beam 4 whichis situated at the edge in the x-y plane relative to a plane defined bythe radiation source S and the axis of rotation 14) then determines thediameter of the examination zone 13 within which the object to beexamined must be present during the acquisition of the measuring values.In order to generate volume images of the object, the object which isarranged, for example, on a table in the examination zone 13, can bedisplaced parallel to the direction of the axis of rotation 14 or the zaxis by means of a motor 5. The measuring data acquired by the detectorunit 16 is applied to a reconstruction unit 10 which reconstructstherefrom the absorption distribution in the part of the examinationzone 13 which is covered by the radiation beam 4. The two motors 2 and5, the reconstruction unit 10, the radiation source S and the transferof the measuring data from the detector unit 16 to the reconstructionunit 10 are controlled by means of a suitable control unit 7.

The motors 2 and 5 can be controlled in such a manner that the ratio ofthe speed of propagation of the examination zone 13 to the angularvelocity of the gantry 1 is constant, so that the radiation source S andthe examination zone 13 move along a helical path, that is, theso-called trajectory, relative to one another. In this case it isirrelevant whether the scanning unit, consisting of the radiation sourceS and the detector unit 16, or the examination zone 13 performs therotary motion or the propagation motion, because only the relativemotion is of importance. The object is not displaced for the formationof slice images.

A motion signal is derived by means of an acquisition unit 12 and amotion sensor 15 which is arranged on the object in order to detect theobject motion. This signal can be applied, if desired, to thereconstruction unit 10 in order to facilitate the selection of themeasuring data that is suitable for the reconstruction. Furthermore, themotion signal is used (as will be described in detail hereinafter) inaccordance with the invention for the determination of the motion model.

Furthermore, a PET acquisition unit 20 is arranged so as to beconcentric with relative to the axis of rotation 14; this unit isarranged as a ring around the object which is present in the examinationzone 13. The acquisition unit 20 comprises individual sensors 21 whichdetect the γ quanta emitted by the object. In order to form sliceimages, it suffices to configure the PET acquisition unit so as to bequasi two-dimensional by arranging sensors 21 adjacent one another in aring-like configuration. In order to generate volume images, the PETacquisition unit comprises a plurality of such rings of sensor which arearranged so as to be parallel to one another and around the axis ofrotation 13. The signals detected by the sensors 21 are applied to anevaluation unit 22 which forms one or more PET images therefrom by meansof known algorithms.

In addition to the above-mentioned functions, the control unit 7 is alsoarranged to displace the object between the acquisition positions of theCT system as well as those of the PET system. After successfulacquisition of the CT data, for example, the object on the table isdisplaced, by means of the control unit 7 and the motor 5, to theacquisition position of the PET acquisition unit 20 in which therelevant preparation is injected into the object and the PET data isacquired.

The data processing unit 23 is arranged to combine, using the method inaccordance with the invention as well as the motion signal, theinformation contents of the CT images and the PET images, to reducemotion artifacts, if any, and to visualize the results accordingly bymeans of a display apparatus 11. If the data processing unit isconstructed so as to be programmable, it is enabled by a computerprogram to carry out the method in accordance with the invention. Thecomputer program may be stored in an internal memory such as, forexample, a ROM or an EPROM, or in a computer program product such as adisc or CD-ROM provided with the computer program.

The computed tomography apparatus shown as well as the PET acquisitionunit may be configured in such a manner that slice as well as volumeimages can be acquired.

The images I2 and I3 of FIG. 1 represent two different states of motionof the motion performed by the object during the acquisition of theprojections P1. Because it is inherent of the method of CT-basedacquisition that significantly less time is required than foracquisition on the basis of PET, instantaneous images can be formed ofthe respiratory motion of the patient, notably the image I2 of theinhaled state and the image I3 of the exhaled state. The inhaled as wellas the exhaled state of motion of the patient represents a particularlycharacteristic state of the respiratory motion. Alternatively, asequence of CT images IS of the respiratory motion can be acquiredduring which the object performs the same motion as during theacquisition of the projections P1. Subsequently, using known methods,the two images I2 and I3 are extracted from the sequence IS. This offersthe advantage that the motion more accurately corresponds to the motionperformed by the object during the acquisition of the projections P1.When the images I2 and I3 are acquired directly, often unnatural orcramped states of motion occur in the patient; such states are not thesame as those occurring during the natural respiratory motion.

From these state of motion images I2 and I3 an object motion model M2 isformed in the step C1 in combination with a state of motion function F1.A state of motion function F1 of this kind is shown in FIG. 4, by way ofexample, as a frequency function f(r) for the human respiratory motion.The y axis of the frequency function f(r) describes how often therelevant states of motion are assumed by the object while it performsthe motion. The x axis represents successive states of motion r assumedwhile the motion is performed. In other words, the frequency functiondescribes how long on average the object stays in a given state ofmotion in relation to the other states of motion while the objectperforms the motion. If the representation is normalized, the integralover this curve produces exactly 1. It is a particularly significantaspect that during the respiratory motion the organs or tissue involvedin the respiratory motion remain particularly frequently or long in theexhaled state (exhalation). If merely the frequency is of interest forthe further steps of the method, the order of the states of motionassumed while the object performs the motion can be ignored and thestates of motion which are plotted on the x axis need not necessarilysucceed one another during the execution of the motion.

Alternatively it is also feasible to utilize a motion state function F1which not only provides information as regards the frequency of theassumed states of motion, but also describes the overall motion process(states of motion as well as their frequency and completion in time).Because such a state of motion function is redundant for the use in thenext steps of this version, however, it suffices to utilize a frequencyfunction as described above.

For known motion processes the state of motion function F1 can bederived from a function model M1 without taking into account the actualmotion. This is possible notably when in most objects a motion processis very similar or the same. For example, when in the case of a humanrespiratory motion the model M1 is formed by the frequency function f(r)of FIG. 1, it can be considered directly as the state of motion functionF1 and be used for determining the motion model M2. Alternatively, theactual motion process can be determined by means of an appropriatesensor S1. In the case of the respiratory motion, for example, therespiratory motion is determined during the acquisition of the PETprojections P1 by means of a respiratory motion sensor provided on thepatient and therefrom the frequency function f(r) or, more generally, astate of motion function F1 is derived for the construction of themotion model M2.

In the step C1 a motion model M2 is derived from the images I2 and I3and the state of motion function F1. Each of the images I2 and I3represents a respective known state of motion of the object, said statesof motion also being present in the state of motion function F1.Assuming that all components of the object move locally linearly duringthe motion process, that is, along straight paths of different directionand length, between the states of motion shown in the images I2 and I3,for each pixel represented in one of the images I2 or I3 or for eachobject component the execution of the motion can be determined by meansof the state of motion function F1. This location-specific motionprocess can be retained in a motion vector field and constitutes, inconjunction with the state of motion function F1, the motion model M2. Amotion vector thus indicates the direction in which and the speed atwhich or the distance over which a pixel or an object component movesduring the execution of the motion between each time two states ofmotion.

Mathematically speaking, a vector field of this kind can be described as{right arrow over (x)}₂={right arrow over (x)}₃+{right arrow over(m)}({right arrow over (x)}₃). A point {right arrow over (x)}₃ movestowards the point {right arrow over (x)}₂ during the execution of themotion; the motion is characterized by the motion vector field {rightarrow over (m)}({right arrow over (x)}₃) and each state of motion can beapproximated by {right arrow over (x)}(r)={right arrow over(x)}₃+r{right arrow over (m)}({right arrow over (x)}₃). The parameterrε[0,1] represents for r=0 the state of motion represented in the imageI3, where {right arrow over (x)}(r=0)={right arrow over (x)}₃ and forr=1 the state of motion {right arrow over (x)}(r=1)={right arrow over(x)}₂ shown in the image I2. For the human respiratory motion, forexample, {right arrow over (x)}₃ describes the exhaled state and {rightarrow over (x)}₂ describes the inhaled state. Generally speaking, such amathematical description can also be applied to a variety of othermotions. The motion need not be inherently periodic and be repeated.FIG. 5 shows the frequency function of a motion of an object in whichall states of motion are equally frequently assumed during the executionof the motion. This is the case, for example, for the motion where allparts of the object move in the same direction at a constant speed (forexample, a bicycle rider).

The next step C2 aims to form from the images I2 and I3 an image I4which exhibits substantially the same motion artifacts as the image I0.This is achieved in that, starting from one of the images I2 or I3,first artificial images of the remaining states of motion are formed bymeans of the motion model M2, said artificial images then beingsuperposed so as to form the image I4:${{I4}\left( \overset{->}{x} \right)} = {\int_{0}^{1}{{f(r)}{{I3}\left( {{\overset{->}{x}}_{3} + {r{\overset{->}{m}\left( {\overset{->}{x}}_{3} \right)}}} \right)}{{\mathbb{d}r}.}}}$The image I4 is formed from the integral over all states of motion r ofthe product of the image I3 and the motion vector field ({right arrowover (x)}₃+{right arrow over (m)}({right arrow over (x)}₃)) weighted bythe frequency function f(r), the motion vector field ({right arrow over(x)}₃+{right arrow over (m)}({right arrow over (x)}₃)) and the frequencyfunction f(r) constituting the motion model M2. As a result, the imageI4 represents a superposition of all states of motion weighted by therelevant duration of stay.

Analogously, a theoretical consideration of the formation of the PETimage I0 leads to the result that the PET image I0 also constitutes asuperposition of all states of motion weighted by the relevant durationof stay; this means that it is also formed from the integral over allstates of motion r of the product of an image I0 a (not shown in thiscase) of an initial state of motion, the frequency function f(r) and themotion model ({right arrow over (x)}_(a)+{right arrow over (m)}({rightarrow over (x)}_(a))):${{I0}\left( \overset{->}{x} \right)} = {\int_{0}^{1}{{f(r)}{{I0}_{a}\left( {{\overset{->}{x}}_{a} + {r{\overset{->}{m}\left( {\overset{->}{x}}_{a} \right)}}} \right)}{{\mathbb{d}r}.}}}$

In the ideal case the image I0 a represents the same state of motion asthe image I3 and the vectors {right arrow over (x)}_(a) and {right arrowover (x)}₃ as well as the relevant frequency function and the motionmodel correspond. This consideration of the formation of the image I0 isused in the focusing step described hereinafter, because the appearanceof the motion artifacts in the image I0 is thus substantiated.

As an alternative for a combination apparatus as shown in FIG. 6, theimages I0 as well as the images I2 and I3 can be acquired by means oftwo independent systems. The object is then positioned in the firstapparatus, for example, the PET system, and the PET image is acquired.Subsequently, the object is positioned in the second system and the CTimages are acquired. Because of the local separation of the two systems,the object components in the PET image I0 usually are localizeddifferently from those in the CT images I2, I3 and I4, so that only aninadequate direct superposition or direct comparison of the images I4and I0 can be performed. Therefore, in a step R2 a so-calledregistration operation is performed. The step R2 is optional and is notnecessary when the co-ordinate system of the images I0 suitablyaccurately corresponds to that of the images I2 and I3 (as is the casein the system shown in FIG. 6). I0 can then be equalized with I5 and themethod can be continued as described hereinafter.

Registration is a generally known method of equalizing co-ordinatesystems between two or more images with corresponding structures; aphysical correspondence of two identical objects of different contentsmay then also occur. This is the case, for example, for a functional PETimage and an anatomical CT image of the same object. After successfulregistration, the object parts represented in one image can beassociated with the corresponding object parts in the other image by theco-ordinate transformation determined. As a result, for example, theobject parts shown in one image can be shifted in such a manner thatthey occupy the corresponding positions of the identical object partsrepresented in the other image.

The article by D. Mattes et al. “Nonrigid multimodality imageregistration”, Medical Imaging 2001: Image Processing, Proceedings ofSPIE Vol. 4322 (2001) describes how such a registration of a CT imageand a PET image can be carried out. Because the registration isgenerally known, it will not be further elaborated herein. It is to benoted, however, that in order to facilitate the registration in knownPET systems, a transmission image is acquired in addition to the actualPET image as is also mentioned in the cited article. Prior to theinjection of the metabolic preparation marked with nuclides, aradioactive source is displaced along a trajectory around the patientfor this purpose, said source emitting rays in the direction of thepatient which penetrate the patient and are detected by sensors of thePET detector which are situated opposite the radiation source. Thetransmission image subsequently reconstructed is in principle similar toa CT image and, because of the anatomical information contained therein,is better suitable for registration with the CT image, notably in thecase of a poor image quality of the actual PET image. When theco-ordinate transformation between the transmission image and the CTimage has been determined, the co-ordinates of the actual PET image andthe CT image can be made to correspond, because the co-ordinate systemsof the transmission image and the PET image are substantially identical.This method is not shown in FIG. 1, but can nevertheless be used herein.

After successful registration R2, the pixels or the object components ofthe image I0 can be transformed in the co-ordinate system of the imageI4. This produces the PET image I5. A possible alternative, that is,transforming the image I4 into the co-ordinate system of the image I0,will not be elaborated herein. A comparison or a combination of theimages I4 and I5 can now be performed, because both images exhibitsubstantially the same motion artifacts of the object motion and bothimages represent the object in relation to the same co-ordinate system.A viewer, for example, a physician, may desire the presentation of theimage I0 without falsifications (a co-ordinate transformation in thissense does not represent a falsification) for given applications so asto enable comparison or combination of information therefrom withinformation from other images. Prior art merely offers the possibilityof comparing or combining only one of the two images I2 or I3 directlywith the image I0. As opposed to the image I0, the images I2 or I3 donot exhibit motion artifacts, so that on the one hand the searching of asuitable co-ordinate transformation is more difficult and on the otherhand the combination or comparison itself is possible only withdifficulty.

Such comparisons or combinations as shown as the step R3 in FIG. 1 areknown in principle and can be realized, for example, by superposition,by adjacently arranged images, by partial superposition with manuallyselectable boundaries or by partial imaging of one image in the otherimage with manually selectable boundaries. The result of the step R3constitutes the image I6.

In dependence on the relevant application, it may be useful for a userof the system to limit the image I6 to given information or to highlightgiven information in particular. To this end, an optional step B1 can beperformed for focusing the image I6 which contains artifacts and inwhich only one state of motion of the motion is represented. A knownalgorithm for focusing which is suitable for linear motions is describedin the article by A. K. Katsaggelos “Iterative image restorationalgorithms”, OPTICAL ENGINEERING, July 1989, Vol. 28, No. 7, p. 735 ff.Notably the equation (1) shows how motional unsharpness can in generalbe expressed by modeling the motion to a linear motion and becompensated in the further course of the method.

FIG. 2 shows a further version of the method in accordance with theinvention in a combination system. As in FIG. 1, again a motion model M2is determined and also a PET image I0 is formed. The registration R2shown in FIG. 1 is dispensed with, because the correspondence of theco-ordinate systems of the images I0, I2 and I3 is adequate.

In a step B2, analogous to the step B1 of FIG. 1, focusing of the imageI0 is carried out. As opposed to the focusing in FIG. 1, the focusing B2of FIG. 2 is carried out in such a manner that the sharper PET image I8represents the same state of motion as an acquired CT image, in thiscase the image I2. As a result, the image I8 can be compared or combineddirectly with an original CT image, in this case being the image I2.Alternatively, this process can also be carried out by means of theimage I3 or an image from the image sequence IS. In the comparison stepR4 the same methods are used as described with reference to FIG. 1, stepR3. The image I9 is the resultant image.

An alternative for the method of FIG. 2 (not shown) is to apply thefocusing B1 to the image I5 instead of to the combination image I6 inFIG. 1 when the co-ordinate systems of the image I0 and the images I2and I3 are different. As a result of the previously executedregistration R2 it is first achieved that the co-ordinate system of theimage I5 corresponds to that of the image I4 and hence to that of themotion model M2. This enables focusing B1 of the image I5 by means ofthe motion model M2. The resultant image is a PET image which representsa state of motion of the motion and contains practically no motionartifacts.

FIG. 3 shows a further possibility for enhancing the informationcontents of an image by means of the motion model. In known PET systemsa transmission image is acquired by means of the above method, that is,in addition to the actual PET image. This transmission image representsthe location-specific attenuation of the radioactive radiation. Thisattenuation information is used for the reconstruction R1 of theprojections P1 in order to correct the absorption of γ quanta bysurrounding tissue (attenuation correction). In the article by I. T.Hsiao et al. “Noise Propagation from Attenuation Correction into PETReconstructions” (published in “Nuclear Science & Medical Imagingincluding Nuclear Power Systems, 2000 Symposium”, IEEE, ISBN0-7803-6503-8) various methods are disclosed, for example, in Table 1,for the correction of the location-specific attenuation. Equation (4)reveals a possibility for multiplying the reconstruction, expressed as alinear reconstruction operator, by the location-specific attenuationinformation while taking into account distribution effects.

These methods, however, have the drawback that the transmission image,as opposed to the actual PET image, often contains only few or even nomotion artifacts, because the acquisition time is short in comparisonwith the duration of the motion. As a result, the attenuationinformation is not appropriately used and the motion artifacts in thePET image, due to the above-mentioned cause 2, are not taken intoaccount.

Therefore, in accordance with the invention the reconstruction R5 of thePET image I10 utilizes a transmission image I4 which is formed, as inFIG. 1, from the CT images I2 and I3 as well as the motion model M2. Theimage I4 contains substantially the same motion artifacts as a PET imagewhich is reconstructed without any attenuation information. As a result,the motion artifacts in the PET image are taken into account and thereconstruction R5 using the attenuation information from the image I4produces a qualitatively enhanced image I10 in comparison with areconstruction utilizing a conventional transmission image.

Generally speaking, the methods of the FIGS. 1, 2 and 3 can also besimultaneously used in a system so as to enable presentation of thevarious results of the methods to a viewer. The method of FIG. 3 can becombined at will with the methods of FIG. 1 and FIG. 2, that is, for aslong as the system used is a combination system, because the co-ordinatesystems of the PET system correspond substantially to those of the CTsystem only in the case of a combination system.

It is to be noted again that the methods shown in FIG. 1, FIG. 2 andFIG. 3 are not limited to CT and PET. For example, it is possible toacquire the image I0 by means of magnetic resonance tomography insteadof a PET-based method or, alternatively, to acquire the images I2 and I3by means of ultrasound or fast magnetic resonance tomography instead ofby means of a CT-based method. Because the method in accordance with theinvention in general offers a possibility for comparing imagescontaining different information on a moving object, while taking intoaccount motion artifacts present in an image, applications outside themedical field are also feasible. For example, an image of a travelingcar which contains motion artifacts can be acquired by means of athermal-sensitive camera and further images can be acquired by means ofcustomary photographic methods. The image of the thermal-sensitivecamera shows location-specific functional processes, whereas thephotographic images represent structural features of the object. Thesuperposition of such different types of information so as to form acombination image while taking into account the motion artifactsadvantageously enables the presentation of all informationsimultaneously to a viewer.

1. A method of enhancing the information contents which can be derivedfrom a first image, containing motion artifacts, of a moving object,which method includes the following steps: a. using two further imageswhich represent the object in a respective state of motion with as fewmotion artifacts as possible, b. determining a motion model whichcharacterizes states of motion assumed by the object while performingthe motion between the two states of motion, c. forming an intermediateimage of the object from the motion model and the two further images,the intermediate image representing the object at least approximately asif it had performed the motion, d. forming a combination image from theintermediate image and the first image.
 2. A method of enhancing theinformation contents which can be derived from a first image, containingmotion artifacts, of a moving object, which method includes thefollowing steps: a. using two further images which represent the objectin a respective state of motion with as few motion artifacts aspossible, b. determining a motion model which characterizes states ofmotion assumed by the object while performing the motion between the twostates of motion, c. focusing the first image by means of the motionmodel.
 3. A method of enhancing the information contents which can bederived from a first image, to be reconstructed from projections andcontaining motion artifacts, of a moving object, which method includesthe following steps: a. using two further images which represent theobject in a respective state of motion with as few motion artifacts aspossible, b. determining a motion model which characterizes states ofmotion assumed by the object while performing the motion between the twostates of motion, c. forming an intermediate image of the object fromthe motion model and the two further images, the intermediate imagerepresenting the object at least substantially as if it had performedthe motion, d. reconstructing the first image from the projections ofthe object and the intermediate image.
 4. A method as claimed in claim 1wherein a respective motion vector field is determined for parts of theobject in order to determine the motion model.
 5. A method as claimed inclaim 1, wherein in order to form the intermediate image, first imagesof other states of motion of the object are formed by means of the twofurther images and the motion model, the images thus formed beingweighted and subsequently superposed together with the two furtherimages and in conformity with the frequency at which the respectivestate of motion represented in the images occurs while the motion isperformed.
 6. A method as claimed in claim 1, wherein the intermediateimage and the first image are registered, notably elasticallyregistered, prior to the formation of the combination image.
 7. A methodas claimed in claim 1, wherein the combination image is focused in afurther step.
 8. A method as claimed in claim 2, wherein a combinationimage is formed from the focused first image and one of the two furtherimages, possibly by means of registration.
 9. A method as claimed in theclaim 1, wherein the image is a PET image or a SPECT image and the twofurther images are one of CT images and MR images.
 10. An imageprocessing system which includes a data processing unit for carrying outa method as claimed in claim
 1. 11. An examination apparatus, notably amedical examination apparatus, which includes a device for formingimages and/or projections by means of a first imaging method, a devicefor forming images and/or projections by means of a second imagingmethod, an image processing system which includes a data processing unitfor carrying out a method as claimed in claim
 1. 12. A computer readablemedium containing instructions for controlling a data processing unit insuch a manner that the data processing unit can carry out a method asclaimed in claim
 1. 13. A method as claimed in claim 2 wherein arespective motion vector field is determined for parts of the object inorder to determine the motion model.
 14. A method as claimed in claim 3wherein a respective motion vector field is determined for parts of theobject in order to determine the motion model.
 15. A method as claimedin claim 2 wherein in order to form the intermediate image, first imagesof other states of motion of the object are formed by means of the twofurther images and the motion model the images thus formed beingweighted and subsequently superposed together with the two furtherimages and in conformity with the frequency at which the respectivestate of motion represented in the images occurs while the motion isperformed.
 16. A method as claimed in claim 3 wherein in order to formthe intermediate image, first images of other states of motion of theobject are formed by means of the two further images and the motionmodel, the images thus formed being weighted and subsequently superposedtogether with the two further images and in conformity with thefrequency at which the respective state of motion represented in theimages occurs while the motion is performed.
 17. A method as claimed inclaim 2 wherein the image is a PET image or a SPECT image and the twofurther images are one of CT images and MR images.
 18. A method asclaimed in claim 3 wherein the image is a PET image or a SPECT image andthe two further images are one of CT images and MR images.